Google, on October 17, announced new collaborations across India's health, sustainability, and agriculture sectors that will deploy the company's artificial intelligence (AI) research and models across a range of applications—from helping to prevent blindness among people with diabetes to supporting field-level insights that benefit farmers and reducing strain on the country's landfills.
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According to Google, these announcements were made during a roundtable in Bengaluru, marking the fifth anniversary of Google's Research Lab in the city. This follows the 10th edition of the Google for India event, which showcased the potential of AI.
"At Google, we're not just building AI, but are helping shape a future where AI benefits everyone. Collaborating with key Indian organisations, our focused research in India across language understanding, healthcare, agriculture and sustainability is helping tackle many of the country's unique challenges and creating AI-led solutions that will improve billions of lives," said Dr Manish Gupta, Research Director, Google DeepMind, according to an ANI report.
Diabetic Retinopathy
Google said it started exploring the potential for AI to screen for diabetic retinopathy and help prevent blindness through early detection, eventually conducting the first patient screening in Madurai, India.
"Since then, our diabetic retinopathy AI model has helped support more than 600,000 screenings in clinics around the world. The model supports clinicians with early detection at scale, and in turn assisting timely medical intervention," Google said in a blog post.
Google has licensed this AI model to healthcare providers and health-tech partners Forus Health and AuroLab in India, as well as Perceptra in Thailand, to provide approximately 6 million AI-assisted screenings for diabetic retinopathy in resource-constrained communities in India and Thailand over the next 10 years.
K Chandrasekhar, Founder and CEO, Forus Health: "Forus Health is thrilled to partner with Google to bring AI-powered diabetic retinopathy screening to the forefront of eye care by leveraging our innovative retinal cameras and platform. We are confident of impacting millions of lives and fulfil our mission of eliminating preventable blindness."
R D Sriram, Managing Director, AuroLab: "It has been great to see the multiple phases of Google’s diabetic retinopathy AI model - from development to validation to deployment. At AuroLab, we are hopeful that this AI model will play a crucial role in preventing unnecessary vision loss for millions of people."
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Supporting Plastic Recycling
Google's CircularNet, an open-source machine-learning and AI computer vision model for waste management, is being deployed in partnership with Bengaluru-based Saahas Zero Waste.
According to Google, CircularNet provides pixel-level instance segmentation, characterising plastic materials by form and type to improve how they are sorted, managed, and recycled across the entire waste management cycle.
Saahas Zero Waste (SZW) has been leveraging CircularNet in its efforts to sort plastic waste, improve recycling, reduce strain on landfills from recyclable waste, and strengthen India's circular economy, according to Google.
CircularNet supports SZW as a vision-based quality control system that checks the quality and quantity of waste before it is sorted, baled, and sent to recycling centers, as well as when it is received at those centers, Google explained.
In a pilot of CircularNet's AI model at its material recycling facility, Saahas Zero Waste estimates that it achieved approximately 85 percent accuracy in detecting plastic waste. Based on these internal evaluations, SZW predicts that the higher quality of recyclable materials recovered could translate into a 10-12 percent improvement in revenue generation. Saahas Zero Waste has further estimated that roughly 90 percent of recyclable waste could be diverted from landfills.
Arun Murugesh, Vice President, Sales and Marketing, Saahas Zero Waste: "Google's CircularNet model is playing an important role by supporting automated AI-powered quality control systems that can be deployed efficiently at scale - and we’ve been greatly encouraged by early results. Improved quality assurance at waste recovery facilities and recyclers powered by CircularNet promises to improve resource recovery through closed loop recycling.
"By combining technology with viable business models, we aim to contribute towards India's vision of a circular economy. We also see AI-assisted partnerships as a driver to achieving larger impact, including livelihood generation, safer working conditions and greater ecological conscientiousness."
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Opened ALU API to Developers
To support data-driven decision-making in agriculture, Google is also opening its Agricultural Landscape Understanding (ALU) Research API to developers. The ALU API uses remote sensing and AI to provide insights at the individual farm level across India. By combining satellite imagery with machine learning models, the ALU API can identify fields, water bodies, and vegetation boundaries and their acreage, organising agricultural information and providing it as a base layer for the agri-ecosystem.
These technological capabilities can assist in making more data-driven and efficient decisions across India's agri-ecosystem, while supporting the development of precision agriculture tools, optimising resource allocation, and improving agricultural practices that help farmers enhance farm management and productivity, Google said.
